The liver tumor segmentation benchmark (lits) P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical Image Analysis 84, 102680, 2023 | 1113 | 2023 |
Automatic detection of new tumors and tumor burden evaluation in longitudinal liver CT scan studies R Vivanti, A Szeskin, N Lev-Cohain, J Sosna, L Joskowicz International journal of computer assisted radiology and surgery 12, 1945-1957, 2017 | 81 | 2017 |
Automated evaluation of human embryo blastulation and implantation potential using deep‐learning Y Kan-Tor, N Zabari, I Erlich, A Szeskin, T Amitai, D Richter, Y Or, ... Advanced Intelligent Systems 2 (10), 2000080, 2020 | 28 | 2020 |
Automatic detection and diagnosis of sacroiliitis in CT scans as incidental findings Y Shenkman, B Qutteineh, L Joskowicz, A Szeskin, A Yusef, A Mayer, ... Medical image analysis 57, 165-175, 2019 | 25 | 2019 |
A column-based deep learning method for the detection and quantification of atrophy associated with AMD in OCT scans A Szeskin, R Yehuda, O Shmueli, J Levy, L Joskowicz Medical Image Analysis 72, 102130, 2021 | 16 | 2021 |
Liver lesion changes analysis in longitudinal CECT scans by simultaneous deep learning voxel classification with SimU-Net A Szeskin, S Rochman, S Weiss, R Lederman, J Sosna, L Joskowicz Medical Image Analysis 83, 102675, 2023 | 14 | 2023 |
Progression of cRORA (complete RPE and outer retinal atrophy) in dry age-related macular degeneration measured using SD-OCT O Shmueli, R Yehuda, A Szeskin, L Joskowicz, J Levy Translational Vision Science & Technology 11 (1), 19-19, 2022 | 14 | 2022 |
Copper interconnections and antennas fabricated by hot-pressing printed copper formate YS Rosen, Y Lidor, R Balter, A Szeskin, A Awadallah, ... Flexible and Printed Electronics 2 (3), 035007, 2017 | 9 | 2017 |
Graph-based automatic detection and classification of lesion changes in pairs of CT studies for oncology follow-up S Rochman, A Szeskin, R Lederman, J Sosna, L Joskowicz International Journal of Computer Assisted Radiology and Surgery 19 (2), 241-251, 2024 | 3 | 2024 |
Follow-up of liver metastases: a comparison of deep learning and RECIST 1.1 L Joskowicz, A Szeskin, S Rochman, A Dodi, R Lederman, ... European Radiology 33 (12), 9320-9327, 2023 | 3 | 2023 |
Measuring Geographic Atrophy Area Using Column-Based Machine Learning Software on Spectral-Domain Optical Coherence Tomography versus Fundus Auto Fluorescence O Shmueli, A Szeskin, I Benhamou, L Joskowicz, Y Shwartz, J Levy Bioengineering 11 (8), 849, 2024 | | 2024 |
Simultaneous column-based deep learning progression analysis of atrophy associated with AMD in longitudinal OCT studies A Szeskin, R Yehuda, O Shmueli, J Levy, L Joskowicz arXiv preprint arXiv:2307.16559, 2023 | | 2023 |
Automated Testing of Graphics Units by Deep-Learning Detection of Visual Anomalies L Faivishevsky, A Szeskin, AK Muppalla, SZ Ravid, I Ben Ari, R Laperdon, ... Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | | 2021 |
cRORA progression and its baseline predicting factors O Shmueli, R Yehuda, A Szeskin, L Joskowicz, J Levy Investigative Ophthalmology & Visual Science 62 (8), 1888-1888, 2021 | | 2021 |
Deep learning using embryo preimplantation videos can automatically predict the potential of human embryos to blastulate and implant Y Ken-Tor, N Zabari, A Szeskin, A Tamar, D Richter, Y Or, Z Shoham, ... HUMAN REPRODUCTION 35, 103-104, 2020 | | 2020 |
A Weak Supervision Approach to Detecting Visual Anomalies for Automated Testing of Graphics Units A Szeskin, L Faivishevsky, AK Muppalla, A Armon, T Hope NeurIPS 2019, ML4SYS, 2019 | | 2019 |